Problem Set 6 Solutions

Size: px
Start display at page:

Download "Problem Set 6 Solutions"

Transcription

1 6.04/18.06J Mathmatics for Computr Scic March 15, 005 Srii Dvadas ad Eric Lhma Problm St 6 Solutios Du: Moday, March 8 at 9 PM Problm 1. Sammy th Shar is a fiacial srvic providr who offrs loas o th followig trms. Sammy loas a clit m dollars i th morig. This puts th clit m dollars i dbt to Sammy. Each vig, Sammy first chargs a srvic f, which icrass th clit s dbt by f dollars, ad th Sammy chargs itrst, which multiplis th dbt by a factor of p. For xampl, if Sammy s itrst rat wr a modst 5% pr day, th p would b (a) What is th clit s dbt at th d of th first day? Solutio. At th d of th first day, th clit ows Sammy (m + f)p = mp + fp dollars. (b) What is th clit s dbt at th d of th scod day? Solutio. ((m + f)p + f)p = mp + fp + fp (c) Writ a formula for th clit s dbt aftr d days ad fid a quivalt closd form. Solutio. Th clit s dbt aftr thr days is (((m + f)p + f)p + f)p = mp 3 + fp 3 + fp + fp. Gralizig from this pattr, th clit ows d d mp + fp dollars aftr d days. Applyig th formula for a gomtric sum givs: d+1 d p 1 mp + f 1 p 1 Problm. Fid closd form xprssios qual to th followig sums. Show your wor. =1

2 Problm St 6 (a) 9 i 7 i i=0 11 i Solutio. Split th xprssio ito two gomtric sris ad th apply th formula for th sum of a gomtric sris. i 9 i 7 i 9 7 i = 11 i i=0 i=0 i= = = (b) i=1 3 4i+5 Solutio. Taig th logarithm rducs this product to a asy sum. 3 log 3( Q 3 4i+5 = i=1 34i+5 ) i=1 P = 3 i=1 4i+5 = 3 (+1)+5 (c) 1 j 5/3 1 j 1/3 j=1 i=0 i Solutio. This farsom looig sum is a papr tigr; w just apply th formula for th sum of a gomtric sris followd by th formula for th sum of a arithmtic sris. i 1 1 j 5/3 1 = j 5/3 j 1/3 j=1 i=0 j=1 1 1 j 1/3 = j = j=1 1 ( + )( + 1) 3 1

3 Problm St 6 3 Problm 3. Thr is a bug o th dg of a 1 mtr rug. Th bug wats to cross to th othr sid of th rug. It crawls at 1 cm pr scod. Howvr, at th d of ach scod, a malicious first gradr amd Mildrd Adrso strtchs th rug by 1 mtr. Assum that hr actio is istataous ad th rug strtchs uiformly. Thus, hr s what happs i th first fw scods: Th bug wals 1 cm i th first scod, so 99 cm rmai ahad. Mildrd strtchs th rug by 1 mtr, which doubls its lgth. So ow thr ar cm bhid th bug ad 198 cm ahad. Th bug wals aothr 1 cm i th xt scod, lavig 3 cm bhid ad 197 cm ahad. Th Mildrd stris, strtchig th rug from mtrs to 3 mtrs. So thr ar ow 3 (3/) = 4.5 cm bhid th bug ad 197 (3/) = 95.5 cm ahad. Th bug wals aothr 1 cm i th third scod, ad so o. Your job is to dtrmi this poor bug s fat. (a) Durig scod i, what fractio of th rug dos th bug cross? Solutio. Durig scod i, th lgth of th rug is 100i cm ad th bug crosss 1 cm. Thrfor, th fractio that th bug crosss is 1/100i. (b) Ovr th first scods, what fractio of th rug dos th bug cross altogthr? Solutio. Th bug crosss 1/100 of th rug i th first scod, 1/00 i th scod, 1/300 i th third, ad so forth. Thus, ovr th first scods, th fractio crossd by th bug is: 1 = H / =1 (This formula is valid oly util th bug rachs th far sid of th rug.) (c) Approximatly how may scods dos th bug d to cross th tir rug? Solutio. Th bug arrivs at th far sid wh th fractio it has crossd rachs 1. This occurs wh, th umbr of scods lapsd, is sufficitly larg that H / Now H is approximatly l, so th bug arrivs about wh: l l scods

4 4 Problm St 6 Problm 4. Us itgratio to fid lowr ad uppr bouds o th followig ifiit sum that diffr by at most 0.1. Show your wor S = To achiv this accuracy, add up th first fw trms xplicitly ad th us itgratio to boud all rmaiig trms. Solutio. Th sum of th first thr trms is: s = + + = A uppr boud o th rmaiig trms is: 1 1 dx = 3 x 3 Ad a lowr boud is: 1 1 dx = (x + 1) 4 3 Ovrall, w hav: = S Ths bouds diffr by 1/1 < 0.1. Th actual valu of th sum is π /6, though th proof is ot asy. Problm 5. A sasod MIT udrgraduat ca: Complt a problm st i days. Writ a papr i days. Ta a day road trip. Study for a xam i 1 day. Play foosball for a tir day. A day schdul is a squc of activitis that rquir a total of days. For xampl, hr ar thr possibl 7 day schduls: pst, papr, pst, foosball papr, study, foosball, pst, study road trip, road trip, road trip, study

5 Problm St 6 5 (a) Exprss th umbr of possibl day schduls usig a rcurrc quatio ad sufficit bas cass. Solutio. S(0) = 1, S(1) =. Ay schdul for > 1 days ds with o of 3 possibl day activitis or o of possibl 1 day activitis. So S() = S( 1) + 3S( ) for > 1. (b) Fid a closd form xprssio for th umbr of possibl day schduls by solvig th rcurrc. Solutio. Th charactristic polyomial for this liar homogous rcurrc is x x 3 = (x + 1)(x 3). Hc th solutio is of th form S() = a( 1) + b3. Lttig = 0, w coclud that a+b = 1, ad lttig = 1, w coclud a+3b =, so b = 3/4, a = 1/4, ad th solutio is: ( 1) S() =. 4 Problm 6. Fid a closd form xprssio for T (), which is dfid by th followig rcurrc: T (0) = 0 T (1) = 1 T () = 5T ( 1) 6T ( ) + 6 for all Solutio. Th charactristic quatio is x 5x + 6 = 0, which has roots x = ad x = 3. Thus, th homogous solutio is: T () = A + B 3 For a particular solutio, lt s first guss T () = c: c = 5c 6c + 6 c = 3 Our guss was corrct; T () = 3 is a particular solutio. Addig this to th homogous solutio givs th gral solutio: T () = A + B 3 + 3

6 6 Problm St 6 Substitutig = 0 ad = 1 givs: 0 = A + B = A + 3B + 3 Solvig this systm givs A = 7 ad B = 4. Thrfor: T () = Problm 7. Dtrmi which of ths choics Θ(), Θ( log ), Θ( ), Θ(1), Θ( ), Θ( l ), o of ths dscribs ach fuctio s asymptotic bhavior. Proofs ar ot rquird, but brifly xplai your aswrs. (a) + l + (l ) Solutio. Both > l ad > (l ) hold for all sufficitly larg. Thus, for all sufficitly larg : < + l + (l ) < + + So + l + (l ) = Θ(). (b) Solutio. Obsrv that: + 3 lim = 1 7 This mas, that for all sufficitly larg, th fractio lis, for xampl, btw, 0.99 ad 1.01 ad is thrfor Θ(1). (c) i=0 i+1 Solutio. Gomtric sums ar domiatd by thir largst trm, which is +1 = 4. This is Θ(4 ), which dos ot appar i th list providd. (d) l(!) Solutio. By Stirlig s formula:! π

7 Problm St 6 7 Taig logarithms givs: l(!) l( π ) = l( π ) + l Th first trm is tiy compard to th scod, which w ca rwrit as: l = l = Θ( l ) () 1 1 =1 Solutio. Th xprssio i parthss is always at last 1/ ad at most 1. Thus, w hav th bouds: =1 =1 =1 Sic th first xprssio ad th last ar both Θ( ), so is th o i th middl. Problm 8. A triagular umbr is a itgr of th form whr is a positiv itgr. = = ( + 1) (a) Dscrib a solutio to th four pg Towrs of Haoi puzzl with ( + 1)/ diss that rquirs T movs, whr: Solutio. T 1 = 1 T = T Mov all but th largst diss to aothr pg rcursivly. This rquirs T ( 1) movs. Mov th largst diss to aothr pg usig th thr pg stratgy. This rquirs 1 movs. Now mov all th othr diss o top of th largst diss rcursivly. This rquirs T ( 1) movs.

8 8 Problm St 6 Thus, with this stratgy, th total umbr of movs rquird to mov a stac of ( + 1)/ diss is T () = T ( 1) + 1. (b) Fid a closd form xprssio qual to T. Solutio. This is a ihomogous liar quatio. Lt s bgi by tryig to fid a particular solutio. Thr is both a xpotial trm ( ) ad a costat trm, so w might guss somthig of th form a + c: a + c = (a 1 + c) + 1 = (a + 1) + c 1 0 = + (c 1) Evidtly, th costat trm is c = 1, but th xpotial part is mor complicatd. Our rcip says w should xt try a particular solutio of th form a + b + 1: a + b + 1 = (a 1 + b( 1) 1 + 1) + 1 = (a b + 1) + b 1 Equatig th cofficits of th trms givs a = a b + 1, which implis b = 1. Thus, a + +1 is a particular solutio for all a. As log as w hav this dgr of frdom, w might as wll choos a so this solutio is cosistt with th boudary coditio T 1 = 1ad b do: a = 1 a = 1 Thrfor, th solutio to th rcurrc is T = ( 1) + 1. (c) Approximatly how may movs ar rquird to solv th four pg, dis Towrs of Haoi puzzl as a fuctio of? Assum is a triagular umbr. (For styl poits, ma corrct us of asymptotic otatio.) 1 Solutio. W hav = ( ) = + O(1). So th umbr of movs rquird is Θ( ).

TIME VALUE OF MONEY: APPLICATION AND RATIONALITY- AN APPROACH USING DIFFERENTIAL EQUATIONS AND DEFINITE INTEGRALS

TIME VALUE OF MONEY: APPLICATION AND RATIONALITY- AN APPROACH USING DIFFERENTIAL EQUATIONS AND DEFINITE INTEGRALS MPRA Muich Prsoal RPEc Archiv TIME VALUE OF MONEY: APPLICATION AND RATIONALITY- AN APPROACH USING DIFFERENTIAL EQUATIONS AND DEFINITE INTEGRALS Mahbub Parvz Daffodil Itratioal Uivrsy 6. Dcmbr 26 Oli at

More information

Econ 371: Answer Key for Problem Set 1 (Chapter 12-13)

Econ 371: Answer Key for Problem Set 1 (Chapter 12-13) con 37: Answr Ky for Problm St (Chaptr 2-3) Instructor: Kanda Naknoi Sptmbr 4, 2005. (2 points) Is it possibl for a country to hav a currnt account dficit at th sam tim and has a surplus in its balanc

More information

Question 3: How do you find the relative extrema of a function?

Question 3: How do you find the relative extrema of a function? ustion 3: How do you find th rlativ trma of a function? Th stratgy for tracking th sign of th drivativ is usful for mor than dtrmining whr a function is incrasing or dcrasing. It is also usful for locating

More information

Soving Recurrence Relations

Soving Recurrence Relations Sovig Recurrece Relatios Part 1. Homogeeous liear 2d degree relatios with costat coefficiets. Cosider the recurrece relatio ( ) T () + at ( 1) + bt ( 2) = 0 This is called a homogeeous liear 2d degree

More information

Power Means Calculus Product Calculus, Harmonic Mean Calculus, and Quadratic Mean Calculus

Power Means Calculus Product Calculus, Harmonic Mean Calculus, and Quadratic Mean Calculus Gug Istitut Jourl, Volum 4, No 4, Novmbr 008 H. Vic Do Powr Ms Clculus Product Clculus, Hrmoic M Clculus, d Qudrtic M Clculus H. Vic Do vick@dc.com Mrch, 008 Gug Istitut Jourl, Volum 4, No 4, Novmbr 008

More information

Asymptotic Growth of Functions

Asymptotic Growth of Functions CMPS Itroductio to Aalysis of Algorithms Fall 3 Asymptotic Growth of Fuctios We itroduce several types of asymptotic otatio which are used to compare the performace ad efficiecy of algorithms As we ll

More information

ELASTIC MODULII AND THEIR RELATIONSHIP BY CONSIDERING ANY ARBITRARY ANGLE

ELASTIC MODULII AND THEIR RELATIONSHIP BY CONSIDERING ANY ARBITRARY ANGLE Itratioal Joural of Mchaical girig ad Tcholog (IJMT Volum 7, Issu, March-April 016, pp. 33-38, Articl ID: IJMT_07_0_004 Availabl oli at http://www.iam.com/ijmt/issus.asp?jtp=ijmt&vtp=7&itp= Joural Impact

More information

An Optimal Algorithm for On-line Bipartite Matching. University of California at Berkeley & International Computer Science Institute

An Optimal Algorithm for On-line Bipartite Matching. University of California at Berkeley & International Computer Science Institute A Optimal Algorithm for O-li Bipartit Matchig Richard M. Karp Uivrsity of Califoria at Brkly & Itratioal Computr Scic Istitut Umsh V. Vazirai Uivrsity of Califoria at Brkly Vijay V. Vazirai Corll Uivrsity

More information

5 2 index. e e. Prime numbers. Prime factors and factor trees. Powers. worked example 10. base. power

5 2 index. e e. Prime numbers. Prime factors and factor trees. Powers. worked example 10. base. power Prim numbrs W giv spcial nams to numbrs dpnding on how many factors thy hav. A prim numbr has xactly two factors: itslf and 1. A composit numbr has mor than two factors. 1 is a spcial numbr nithr prim

More information

AP Calculus AB 2008 Scoring Guidelines

AP Calculus AB 2008 Scoring Guidelines AP Calculus AB 8 Scoring Guidlins Th Collg Board: Conncting Studnts to Collg Succss Th Collg Board is a not-for-profit mmbrship association whos mission is to connct studnts to collg succss and opportunity.

More information

Sharp bounds for Sándor mean in terms of arithmetic, geometric and harmonic means

Sharp bounds for Sándor mean in terms of arithmetic, geometric and harmonic means Qian t al. Journal of Inqualitis and Applications (015) 015:1 DOI 10.1186/s1660-015-0741-1 R E S E A R C H Opn Accss Sharp bounds for Sándor man in trms of arithmtic, gomtric and harmonic mans Wi-Mao Qian

More information

GROUP MEDICAL INSURANCE PROPOSAL FORM GROUP MEDICAL INSURANCE PROPOSAL FORM

GROUP MEDICAL INSURANCE PROPOSAL FORM GROUP MEDICAL INSURANCE PROPOSAL FORM Call us: 920012331 www.acig.com.sa Allid Cooprativ Isurac Group (ACIG) شركة املجموعة املتحدة للتاأمني التعاوين ) أ سيج( GROUP MEDICAL INSURANCE GROUP MEDICAL INSURANCE Clit Dtails: - GROUP MEDICAL INSURANCE

More information

SAMPLE QUESTIONS FOR FINAL EXAM. (1) (2) (3) (4) Find the following using the definition of the Riemann integral: (2x + 1)dx

SAMPLE QUESTIONS FOR FINAL EXAM. (1) (2) (3) (4) Find the following using the definition of the Riemann integral: (2x + 1)dx SAMPLE QUESTIONS FOR FINAL EXAM REAL ANALYSIS I FALL 006 3 4 Fid the followig usig the defiitio of the Riema itegral: a 0 x + dx 3 Cosider the partitio P x 0 3, x 3 +, x 3 +,......, x 3 3 + 3 of the iterval

More information

ME 612 Metal Forming and Theory of Plasticity. 6. Strain

ME 612 Metal Forming and Theory of Plasticity. 6. Strain Mtal Forming and Thory of Plasticity -mail: azsnalp@gyt.du.tr Makin Mühndisliği Bölümü Gbz Yüksk Tknoloji Enstitüsü 6.1. Uniaxial Strain Figur 6.1 Dfinition of th uniaxial strain (a) Tnsil and (b) Comprssiv.

More information

Finite Dimensional Vector Spaces.

Finite Dimensional Vector Spaces. Lctur 5. Ft Dmsoal Vctor Spacs. To b rad to th musc of th group Spac by D.Maruay DEFINITION OF A LINEAR SPACE Dfto: a vctor spac s a st R togthr wth a oprato calld vctor addto ad aothr oprato calld scalar

More information

5.4 Exponential Functions: Differentiation and Integration TOOTLIFTST:

5.4 Exponential Functions: Differentiation and Integration TOOTLIFTST: .4 Eponntial Functions: Diffrntiation an Intgration TOOTLIFTST: Eponntial functions ar of th form f ( ) Ab. W will, in this sction, look at a spcific typ of ponntial function whr th bas, b, is.78.... This

More information

Adverse Selection and Moral Hazard in a Model With 2 States of the World

Adverse Selection and Moral Hazard in a Model With 2 States of the World Advrs Slction and Moral Hazard in a Modl With 2 Stats of th World A modl of a risky situation with two discrt stats of th world has th advantag that it can b natly rprsntd using indiffrnc curv diagrams,

More information

A Note on Approximating. the Normal Distribution Function

A Note on Approximating. the Normal Distribution Function Applid Mathmatical Scincs, Vol, 00, no 9, 45-49 A Not on Approimating th Normal Distribution Function K M Aludaat and M T Alodat Dpartmnt of Statistics Yarmouk Univrsity, Jordan Aludaatkm@hotmailcom and

More information

Our aim is to show that under reasonable assumptions a given 2π-periodic function f can be represented as convergent series

Our aim is to show that under reasonable assumptions a given 2π-periodic function f can be represented as convergent series 8 Fourier Series Our aim is to show that uder reasoable assumptios a give -periodic fuctio f ca be represeted as coverget series f(x) = a + (a cos x + b si x). (8.) By defiitio, the covergece of the series

More information

Approximate Counters for Flash Memory

Approximate Counters for Flash Memory Approximat Coutrs for Flash Mmory Jack Cichoń ad Wojcich Macya Istitut of Mathmatics ad Computr Scic Wrocław Uivrsity of Tchology, Polad Abstract Flash mmory bcoms th a vry popular storag dvic Du to its

More information

BASIC DEFINITIONS AND TERMINOLOGY OF SOILS

BASIC DEFINITIONS AND TERMINOLOGY OF SOILS 1 BASIC DEFINITIONS AND TERMINOLOGY OF SOILS Soil i a thr pha atrial hich coit of olid particl hich ak up th oil klto ad void hich ay b full of atr if th oil i aturatd, ay b full of air if th oil i dry,

More information

Category 7: Employee Commuting

Category 7: Employee Commuting 7 Catgory 7: Employ Commuting Catgory dscription This catgory includs missions from th transportation of mploys 4 btwn thir homs and thir worksits. Emissions from mploy commuting may aris from: Automobil

More information

QUANTITATIVE METHODS CLASSES WEEK SEVEN

QUANTITATIVE METHODS CLASSES WEEK SEVEN QUANTITATIVE METHODS CLASSES WEEK SEVEN Th rgrssion modls studid in prvious classs assum that th rspons variabl is quantitativ. Oftn, howvr, w wish to study social procsss that lad to two diffrnt outcoms.

More information

EFFECT OF GEOMETRICAL PARAMETERS ON HEAT TRANSFER PERFORMACE OF RECTANGULAR CIRCUMFERENTIAL FINS

EFFECT OF GEOMETRICAL PARAMETERS ON HEAT TRANSFER PERFORMACE OF RECTANGULAR CIRCUMFERENTIAL FINS 25 Vol. 3 () January-March, pp.37-5/tripathi EFFECT OF GEOMETRICAL PARAMETERS ON HEAT TRANSFER PERFORMACE OF RECTANGULAR CIRCUMFERENTIAL FINS *Shilpa Tripathi Dpartmnt of Chmical Enginring, Indor Institut

More information

Section 11.3: The Integral Test

Section 11.3: The Integral Test Sectio.3: The Itegral Test Most of the series we have looked at have either diverged or have coverged ad we have bee able to fid what they coverge to. I geeral however, the problem is much more difficult

More information

CPS 220 Theory of Computation REGULAR LANGUAGES. Regular expressions

CPS 220 Theory of Computation REGULAR LANGUAGES. Regular expressions CPS 22 Thory of Computation REGULAR LANGUAGES Rgular xprssions Lik mathmatical xprssion (5+3) * 4. Rgular xprssion ar built using rgular oprations. (By th way, rgular xprssions show up in various languags:

More information

Infinite Sequences and Series

Infinite Sequences and Series CHAPTER 4 Ifiite Sequeces ad Series 4.1. Sequeces A sequece is a ifiite ordered list of umbers, for example the sequece of odd positive itegers: 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29...

More information

Trigonometric Form of a Complex Number. The Complex Plane. axis. ( 2, 1) or 2 i FIGURE 6.44. The absolute value of the complex number z a bi is

Trigonometric Form of a Complex Number. The Complex Plane. axis. ( 2, 1) or 2 i FIGURE 6.44. The absolute value of the complex number z a bi is 0_0605.qxd /5/05 0:45 AM Page 470 470 Chapter 6 Additioal Topics i Trigoometry 6.5 Trigoometric Form of a Complex Number What you should lear Plot complex umbers i the complex plae ad fid absolute values

More information

CPU. Rasterization. Per Vertex Operations & Primitive Assembly. Polynomial Evaluator. Frame Buffer. Per Fragment. Display List.

CPU. Rasterization. Per Vertex Operations & Primitive Assembly. Polynomial Evaluator. Frame Buffer. Per Fragment. Display List. Elmntary Rndring Elmntary rastr algorithms for fast rndring Gomtric Primitivs Lin procssing Polygon procssing Managing OpnGL Stat OpnGL uffrs OpnGL Gomtric Primitivs ll gomtric primitivs ar spcifid by

More information

Chapter 5: Inner Product Spaces

Chapter 5: Inner Product Spaces Chapter 5: Ier Product Spaces Chapter 5: Ier Product Spaces SECION A Itroductio to Ier Product Spaces By the ed of this sectio you will be able to uderstad what is meat by a ier product space give examples

More information

Factorials! Stirling s formula

Factorials! Stirling s formula Author s not: This articl may us idas you havn t larnd yt, and might sm ovrly complicatd. It is not. Undrstanding Stirling s formula is not for th faint of hart, and rquirs concntrating on a sustaind mathmatical

More information

FACULTY SALARIES FALL 2004. NKU CUPA Data Compared To Published National Data

FACULTY SALARIES FALL 2004. NKU CUPA Data Compared To Published National Data FACULTY SALARIES FALL 2004 NKU CUPA Data Compard To Publishd National Data May 2005 Fall 2004 NKU Faculty Salaris Compard To Fall 2004 Publishd CUPA Data In th fall 2004 Northrn Kntucky Univrsity was among

More information

CLOUD COMPUTING BUSINESS MODELS

CLOUD COMPUTING BUSINESS MODELS da MODLS Atlir d l iova CLOUD COMPUTING MODLS Chair coomi d l iova - Mourad Zroukhi C d chrch Écoomi t Maagmt Uivrsité d Chair coomi d l iova - da MODLS AGNDA Cloud Computig : What is it? Cloud Dploymt

More information

Assessing the cost of Outsourcing: Efficiency, Effectiveness and Risk

Assessing the cost of Outsourcing: Efficiency, Effectiveness and Risk Assssig th cost of Outsourcig: Efficicy, Effctivss ad Risk Todd Littl Ladark Graphics tlittl@lgc.co Abstract Offshor outsourcig is a popular approach for copais lookig to rduc softwar dvlopt costs. W hav

More information

1. MATHEMATICAL INDUCTION

1. MATHEMATICAL INDUCTION 1. MATHEMATICAL INDUCTION EXAMPLE 1: Prove that for ay iteger 1. Proof: 1 + 2 + 3 +... + ( + 1 2 (1.1 STEP 1: For 1 (1.1 is true, sice 1 1(1 + 1. 2 STEP 2: Suppose (1.1 is true for some k 1, that is 1

More information

CS103A Handout 23 Winter 2002 February 22, 2002 Solving Recurrence Relations

CS103A Handout 23 Winter 2002 February 22, 2002 Solving Recurrence Relations CS3A Hadout 3 Witer 00 February, 00 Solvig Recurrece Relatios Itroductio A wide variety of recurrece problems occur i models. Some of these recurrece relatios ca be solved usig iteratio or some other ad

More information

FIBONACCI NUMBERS: AN APPLICATION OF LINEAR ALGEBRA. 1. Powers of a matrix

FIBONACCI NUMBERS: AN APPLICATION OF LINEAR ALGEBRA. 1. Powers of a matrix FIBONACCI NUMBERS: AN APPLICATION OF LINEAR ALGEBRA. Powers of a matrix We begi with a propositio which illustrates the usefuless of the diagoalizatio. Recall that a square matrix A is diogaalizable if

More information

Lecture 3: Diffusion: Fick s first law

Lecture 3: Diffusion: Fick s first law Lctur 3: Diffusion: Fick s first law Today s topics What is diffusion? What drivs diffusion to occur? Undrstand why diffusion can surprisingly occur against th concntration gradint? Larn how to dduc th

More information

MATH 083 Final Exam Review

MATH 083 Final Exam Review MATH 08 Fial Eam Review Completig the problems i this review will greatly prepare you for the fial eam Calculator use is ot required, but you are permitted to use a calculator durig the fial eam period

More information

http://www.webassign.net/v4cgijeff.downs@wnc/control.pl

http://www.webassign.net/v4cgijeff.downs@wnc/control.pl Assigmet Previewer http://www.webassig.et/vcgijeff.dows@wc/cotrol.pl of // : PM Practice Eam () Questio Descriptio Eam over chapter.. Questio DetailsLarCalc... [] Fid the geeral solutio of the differetial

More information

S. Tanny MAT 344 Spring 1999. be the minimum number of moves required.

S. Tanny MAT 344 Spring 1999. be the minimum number of moves required. S. Tay MAT 344 Sprig 999 Recurrece Relatios Tower of Haoi Let T be the miimum umber of moves required. T 0 = 0, T = 7 Iitial Coditios * T = T + $ T is a sequece (f. o itegers). Solve for T? * is a recurrece,

More information

In nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008

In nite Sequences. Dr. Philippe B. Laval Kennesaw State University. October 9, 2008 I ite Sequeces Dr. Philippe B. Laval Keesaw State Uiversity October 9, 2008 Abstract This had out is a itroductio to i ite sequeces. mai de itios ad presets some elemetary results. It gives the I ite Sequeces

More information

AP Calculus BC 2003 Scoring Guidelines Form B

AP Calculus BC 2003 Scoring Guidelines Form B AP Calculus BC Scorig Guidelies Form B The materials icluded i these files are iteded for use by AP teachers for course ad exam preparatio; permissio for ay other use must be sought from the Advaced Placemet

More information

ITIL & Service Predictability/Modeling. 2006 Plexent

ITIL & Service Predictability/Modeling. 2006 Plexent ITIL & Srvic Prdictability/Modling 1 2 Plxnt Th Company 2001 Foundd Plxnt basd on an Expandd ITIL Architctur, CMMI, ISO, and BS15000 - itdna 2003 Launchd itdna Srvic Offring 2003 John Groom, past Dirctor

More information

Free ACA SOLUTION (IRS 1094&1095 Reporting)

Free ACA SOLUTION (IRS 1094&1095 Reporting) Fr ACA SOLUTION (IRS 1094&1095 Rporting) Th Insuranc Exchang (301) 279-1062 ACA Srvics Transmit IRS Form 1094 -C for mployrs Print & mail IRS Form 1095-C to mploys HR Assist 360 will gnrat th 1095 s for

More information

.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth

.04. This means $1000 is multiplied by 1.02 five times, once for each of the remaining sixmonth Questio 1: What is a ordiary auity? Let s look at a ordiary auity that is certai ad simple. By this, we mea a auity over a fixed term whose paymet period matches the iterest coversio period. Additioally,

More information

AP Calculus AB 2006 Scoring Guidelines Form B

AP Calculus AB 2006 Scoring Guidelines Form B AP Calculus AB 6 Scorig Guidelies Form B The College Board: Coectig Studets to College Success The College Board is a ot-for-profit membership associatio whose missio is to coect studets to college success

More information

IBM Healthcare Home Care Monitoring

IBM Healthcare Home Care Monitoring IBM Halthcar Hom Car Monitoring Sptmbr 30th, 2015 by Sal P. Causi, P. Eng. IBM Halthcar Businss Dvlopmnt Excutiv scausi@ca.ibm.com IBM Canada Cloud Computing Tigr Tam Homcar by dfinition 1. With a gnsis

More information

THE EFFECT OF GROUND SETTLEMENTS ON THE AXIAL RESPONSE OF PILES: SOME CLOSED FORM SOLUTIONS CUED/D-SOILS/TR 341 (Aug 2005) By A. Klar and K.

THE EFFECT OF GROUND SETTLEMENTS ON THE AXIAL RESPONSE OF PILES: SOME CLOSED FORM SOLUTIONS CUED/D-SOILS/TR 341 (Aug 2005) By A. Klar and K. THE EFFECT OF GROUND SETTEMENTS ON THE AXIA RESPONSE OF PIES: SOME COSED FORM SOUTIONS CUED/D-SOIS/TR 4 Aug 5 By A. Klr d K. Sog Klr d Sog "Th Effct of Groud Displcmt o Axil Rspos of Pils: Som Closd Form

More information

Basic Elements of Arithmetic Sequences and Series

Basic Elements of Arithmetic Sequences and Series MA40S PRE-CALCULUS UNIT G GEOMETRIC SEQUENCES CLASS NOTES (COMPLETED NO NEED TO COPY NOTES FROM OVERHEAD) Basic Elemets of Arithmetic Sequeces ad Series Objective: To establish basic elemets of arithmetic

More information

SPREAD OPTION VALUATION AND THE FAST FOURIER TRANSFORM

SPREAD OPTION VALUATION AND THE FAST FOURIER TRANSFORM RESEARCH PAPERS IN MANAGEMENT STUDIES SPREAD OPTION VALUATION AND THE FAST FOURIER TRANSFORM M.A.H. Dmpstr & S.S.G. Hong WP 26/2000 Th Judg Institut of Managmnt Trumpington Strt Cambridg CB2 1AG Ths paprs

More information

(Analytic Formula for the European Normal Black Scholes Formula)

(Analytic Formula for the European Normal Black Scholes Formula) (Analytic Formula for th Europan Normal Black Schols Formula) by Kazuhiro Iwasawa Dcmbr 2, 2001 In this short summary papr, a brif summary of Black Schols typ formula for Normal modl will b givn. Usually

More information

CHAPTER 3 THE TIME VALUE OF MONEY

CHAPTER 3 THE TIME VALUE OF MONEY CHAPTER 3 THE TIME VALUE OF MONEY OVERVIEW A dollar i the had today is worth more tha a dollar to be received i the future because, if you had it ow, you could ivest that dollar ad ear iterest. Of all

More information

Remember you can apply online. It s quick and easy. Go to www.gov.uk/advancedlearningloans. Title. Forename(s) Surname. Sex. Male Date of birth D

Remember you can apply online. It s quick and easy. Go to www.gov.uk/advancedlearningloans. Title. Forename(s) Surname. Sex. Male Date of birth D 24+ Advancd Larning Loan Application form Rmmbr you can apply onlin. It s quick and asy. Go to www.gov.uk/advancdlarningloans About this form Complt this form if: you r studying an ligibl cours at an approvd

More information

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES

SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES SECTION 1.5 : SUMMATION NOTATION + WORK WITH SEQUENCES Read Sectio 1.5 (pages 5 9) Overview I Sectio 1.5 we lear to work with summatio otatio ad formulas. We will also itroduce a brief overview of sequeces,

More information

Abstract. Introduction. Statistical Approach for Analyzing Cell Phone Handoff Behavior. Volume 3, Issue 1, 2009

Abstract. Introduction. Statistical Approach for Analyzing Cell Phone Handoff Behavior. Volume 3, Issue 1, 2009 Volum 3, Issu 1, 29 Statistical Approach for Analyzing Cll Phon Handoff Bhavior Shalini Saxna, Florida Atlantic Univrsity, Boca Raton, FL, shalinisaxna1@gmail.com Sad A. Rajput, Farquhar Collg of Arts

More information

by John Donald, Lecturer, School of Accounting, Economics and Finance, Deakin University, Australia

by John Donald, Lecturer, School of Accounting, Economics and Finance, Deakin University, Australia Studnt Nots Cost Volum Profit Analysis by John Donald, Lcturr, School of Accounting, Economics and Financ, Dakin Univrsity, Australia As mntiond in th last st of Studnt Nots, th ability to catgoris costs

More information

Chapter 6: Variance, the law of large numbers and the Monte-Carlo method

Chapter 6: Variance, the law of large numbers and the Monte-Carlo method Chapter 6: Variace, the law of large umbers ad the Mote-Carlo method Expected value, variace, ad Chebyshev iequality. If X is a radom variable recall that the expected value of X, E[X] is the average value

More information

Foreign Exchange Markets and Exchange Rates

Foreign Exchange Markets and Exchange Rates Microconomics Topic 1: Explain why xchang rats indicat th pric of intrnational currncis and how xchang rats ar dtrmind by supply and dmand for currncis in intrnational markts. Rfrnc: Grgory Mankiw s Principls

More information

81-1-ISD Economic Considerations of Heat Transfer on Sheet Metal Duct

81-1-ISD Economic Considerations of Heat Transfer on Sheet Metal Duct Air Handling Systms Enginring & chnical Bulltin 81-1-ISD Economic Considrations of Hat ransfr on Sht Mtal Duct Othr bulltins hav dmonstratd th nd to add insulation to cooling/hating ducts in ordr to achiv

More information

Convexity, Inequalities, and Norms

Convexity, Inequalities, and Norms Covexity, Iequalities, ad Norms Covex Fuctios You are probably familiar with the otio of cocavity of fuctios. Give a twicedifferetiable fuctio ϕ: R R, We say that ϕ is covex (or cocave up) if ϕ (x) 0 for

More information

Theorems About Power Series

Theorems About Power Series Physics 6A Witer 20 Theorems About Power Series Cosider a power series, f(x) = a x, () where the a are real coefficiets ad x is a real variable. There exists a real o-egative umber R, called the radius

More information

NATIONAL SENIOR CERTIFICATE GRADE 12

NATIONAL SENIOR CERTIFICATE GRADE 12 NATIONAL SENIOR CERTIFICATE GRADE MATHEMATICS P EXEMPLAR 04 MARKS: 50 TIME: 3 hours This questio paper cosists of 8 pages ad iformatio sheet. Please tur over Mathematics/P DBE/04 NSC Grade Eemplar INSTRUCTIONS

More information

4.3. The Integral and Comparison Tests

4.3. The Integral and Comparison Tests 4.3. THE INTEGRAL AND COMPARISON TESTS 9 4.3. The Itegral ad Compariso Tests 4.3.. The Itegral Test. Suppose f is a cotiuous, positive, decreasig fuctio o [, ), ad let a = f(). The the covergece or divergece

More information

A probabilistic proof of a binomial identity

A probabilistic proof of a binomial identity A probabilistic proof of a biomial idetity Joatho Peterso Abstract We give a elemetary probabilistic proof of a biomial idetity. The proof is obtaied by computig the probability of a certai evet i two

More information

Here are a couple of warnings to my students who may be here to get a copy of what happened on a day that you missed.

Here are a couple of warnings to my students who may be here to get a copy of what happened on a day that you missed. This documet was writte ad copyrighted by Paul Dawkis. Use of this documet ad its olie versio is govered by the Terms ad Coditios of Use located at http://tutorial.math.lamar.edu/terms.asp. The olie versio

More information

The example is taken from Sect. 1.2 of Vol. 1 of the CPN book.

The example is taken from Sect. 1.2 of Vol. 1 of the CPN book. Rsourc Allocation Abstract This is a small toy xampl which is wll-suitd as a first introduction to Cnts. Th CN modl is dscribd in grat dtail, xplaining th basic concpts of C-nts. Hnc, it can b rad by popl

More information

Mathematics. Mathematics 3. hsn.uk.net. Higher HSN23000

Mathematics. Mathematics 3. hsn.uk.net. Higher HSN23000 hsn uknt Highr Mathmatics UNIT Mathmatics HSN000 This documnt was producd spcially for th HSNuknt wbsit, and w rquir that any copis or drivativ works attribut th work to Highr Still Nots For mor dtails

More information

Properties of MLE: consistency, asymptotic normality. Fisher information.

Properties of MLE: consistency, asymptotic normality. Fisher information. Lecture 3 Properties of MLE: cosistecy, asymptotic ormality. Fisher iformatio. I this sectio we will try to uderstad why MLEs are good. Let us recall two facts from probability that we be used ofte throughout

More information

Heat (or Diffusion) equation in 1D*

Heat (or Diffusion) equation in 1D* Heat (or Diffusio) equatio i D* Derivatio of the D heat equatio Separatio of variables (refresher) Worked eamples *Kreysig, 8 th Ed, Sectios.4b Physical assumptios We cosider temperature i a log thi wire

More information

Solving Logarithms and Exponential Equations

Solving Logarithms and Exponential Equations Solvig Logarithms ad Epoetial Equatios Logarithmic Equatios There are two major ideas required whe solvig Logarithmic Equatios. The first is the Defiitio of a Logarithm. You may recall from a earlier topic:

More information

Upper Bounding the Price of Anarchy in Atomic Splittable Selfish Routing

Upper Bounding the Price of Anarchy in Atomic Splittable Selfish Routing Uppr Bounding th Pric of Anarchy in Atomic Splittabl Slfish Routing Kamyar Khodamoradi 1, Mhrdad Mahdavi, and Mohammad Ghodsi 3 1 Sharif Univrsity of Tchnology, Thran, Iran, khodamoradi@c.sharif.du Sharif

More information

Numerical and Experimental Study on Nugget Formation in Resistance Spot Welding for High Strength Steel Sheets in Automobile Bodies

Numerical and Experimental Study on Nugget Formation in Resistance Spot Welding for High Strength Steel Sheets in Automobile Bodies rasactios of JWRI, ol.38 (9), No. rasactios of JWRI, ol.38 (9), No. Numrical ad Exprimtal Study o Nuggt Formatio i Rsistac Spot Wldig for High Strgth Stl Shts i Automobil Bodis MA Nishu* ad MURAKAWA Hidkazu**

More information

Chapter 04.05 System of Equations

Chapter 04.05 System of Equations hpter 04.05 System of Equtios After redig th chpter, you should be ble to:. setup simulteous lier equtios i mtrix form d vice-vers,. uderstd the cocept of the iverse of mtrix, 3. kow the differece betwee

More information

UC Berkeley Department of Electrical Engineering and Computer Science. EE 126: Probablity and Random Processes. Solutions 9 Spring 2006

UC Berkeley Department of Electrical Engineering and Computer Science. EE 126: Probablity and Random Processes. Solutions 9 Spring 2006 Exam format UC Bereley Departmet of Electrical Egieerig ad Computer Sciece EE 6: Probablity ad Radom Processes Solutios 9 Sprig 006 The secod midterm will be held o Wedesday May 7; CHECK the fial exam

More information

I. Chi-squared Distributions

I. Chi-squared Distributions 1 M 358K Supplemet to Chapter 23: CHI-SQUARED DISTRIBUTIONS, T-DISTRIBUTIONS, AND DEGREES OF FREEDOM To uderstad t-distributios, we first eed to look at aother family of distributios, the chi-squared distributios.

More information

Planning and Managing Copper Cable Maintenance through Cost- Benefit Modeling

Planning and Managing Copper Cable Maintenance through Cost- Benefit Modeling Planning and Managing Coppr Cabl Maintnanc through Cost- Bnfit Modling Jason W. Rup U S WEST Advancd Tchnologis Bouldr Ky Words: Maintnanc, Managmnt Stratgy, Rhabilitation, Cost-bnfit Analysis, Rliability

More information

Sequences and Series

Sequences and Series CHAPTER 9 Sequeces ad Series 9.. Covergece: Defiitio ad Examples Sequeces The purpose of this chapter is to itroduce a particular way of geeratig algorithms for fidig the values of fuctios defied by their

More information

2-3 The Remainder and Factor Theorems

2-3 The Remainder and Factor Theorems - The Remaider ad Factor Theorems Factor each polyomial completely usig the give factor ad log divisio 1 x + x x 60; x + So, x + x x 60 = (x + )(x x 15) Factorig the quadratic expressio yields x + x x

More information

Approximating Area under a curve with rectangles. To find the area under a curve we approximate the area using rectangles and then use limits to find

Approximating Area under a curve with rectangles. To find the area under a curve we approximate the area using rectangles and then use limits to find 1.8 Approximatig Area uder a curve with rectagles 1.6 To fid the area uder a curve we approximate the area usig rectagles ad the use limits to fid 1.4 the area. Example 1 Suppose we wat to estimate 1.

More information

Find the inverse Laplace transform of the function F (p) = Evaluating the residues at the four simple poles, we find. residue at z = 1 is 4te t

Find the inverse Laplace transform of the function F (p) = Evaluating the residues at the four simple poles, we find. residue at z = 1 is 4te t Homework Solutios. Chater, Sectio 7, Problem 56. Fid the iverse Lalace trasform of the fuctio F () (7.6). À Chater, Sectio 7, Problem 6. Fid the iverse Lalace trasform of the fuctio F () usig (7.6). Solutio:

More information

A Fuzzy Inventory System with Deteriorating Items under Supplier Credits Linked to Ordering Quantity

A Fuzzy Inventory System with Deteriorating Items under Supplier Credits Linked to Ordering Quantity JOURNAL OF INFORMAION SCIENCE AND ENGINEERING 6, 3-53 () A Fuzzy Ivtory Syst with Dtrioratig Its udr Supplir Crdits Likd to Ordrig Quatity LIANG-YUH OUYANG, JINN-SAIR ENG AND MEI-CHUAN CHENG 3 Dpartt of

More information

I. Why is there a time value to money (TVM)?

I. Why is there a time value to money (TVM)? Itroductio to the Time Value of Moey Lecture Outlie I. Why is there the cocept of time value? II. Sigle cash flows over multiple periods III. Groups of cash flows IV. Warigs o doig time value calculatios

More information

Institute of Actuaries of India Subject CT1 Financial Mathematics

Institute of Actuaries of India Subject CT1 Financial Mathematics Istitute of Actuaries of Idia Subject CT1 Fiacial Mathematics For 2014 Examiatios Subject CT1 Fiacial Mathematics Core Techical Aim The aim of the Fiacial Mathematics subject is to provide a groudig i

More information

Incremental calculation of weighted mean and variance

Incremental calculation of weighted mean and variance Icremetal calculatio of weighted mea ad variace Toy Fich faf@cam.ac.uk dot@dotat.at Uiversity of Cambridge Computig Service February 009 Abstract I these otes I eplai how to derive formulae for umerically

More information

GRANT ADMINISTRATION: How Do I Close Out An Expired Grant or Award?

GRANT ADMINISTRATION: How Do I Close Out An Expired Grant or Award? GRANT AMINISTRATION PROCEURES - Scio 6.5 GRANT AMINISTRATION: ow o I Clos Ou A Expird Gr or Awrd? Iroducio Th Niol Isius of lh ( NI ) hs sblishd h followig rquirs for fdrl gr or wrd o b closd ou by isiuios

More information

Rural and Remote Broadband Access: Issues and Solutions in Australia

Rural and Remote Broadband Access: Issues and Solutions in Australia Rural and Rmot Broadband Accss: Issus and Solutions in Australia Dr Tony Warrn Group Managr Rgulatory Stratgy Tlstra Corp Pag 1 Tlstra in confidnc Ovrviw Australia s gographical siz and population dnsity

More information

Running Time ( 3.1) Analysis of Algorithms. Experimental Studies ( 3.1.1) Limitations of Experiments. Pseudocode ( 3.1.2) Theoretical Analysis

Running Time ( 3.1) Analysis of Algorithms. Experimental Studies ( 3.1.1) Limitations of Experiments. Pseudocode ( 3.1.2) Theoretical Analysis Ruig Time ( 3.) Aalysis of Algorithms Iput Algorithm Output A algorithm is a step-by-step procedure for solvig a problem i a fiite amout of time. Most algorithms trasform iput objects ito output objects.

More information

Section 7.4: Exponential Growth and Decay

Section 7.4: Exponential Growth and Decay 1 Sction 7.4: Exponntial Growth and Dcay Practic HW from Stwart Txtbook (not to hand in) p. 532 # 1-17 odd In th nxt two ction, w xamin how population growth can b modld uing diffrntial quation. W tart

More information

Architecture of the proposed standard

Architecture of the proposed standard Architctur of th proposd standard Introduction Th goal of th nw standardisation projct is th dvlopmnt of a standard dscribing building srvics (.g.hvac) product catalogus basd on th xprincs mad with th

More information

Lecture 4: Cauchy sequences, Bolzano-Weierstrass, and the Squeeze theorem

Lecture 4: Cauchy sequences, Bolzano-Weierstrass, and the Squeeze theorem Lecture 4: Cauchy sequeces, Bolzao-Weierstrass, ad the Squeeze theorem The purpose of this lecture is more modest tha the previous oes. It is to state certai coditios uder which we are guarateed that limits

More information

PREFERRED LIFE INSURANCE NORTH AMERICA

PREFERRED LIFE INSURANCE NORTH AMERICA PREFERRED LIFE INSURANCE NORTH AMERICA Dat: Spt, 2011 Ditr Gaubatz Agda 1. Copt 2. History 3. Data 4. Futur 1 Copt No-prfrrd plas Normal mortality risk valuatio pross P r v a l ^ i r a s Issud at stadard

More information

Example 2 Find the square root of 0. The only square root of 0 is 0 (since 0 is not positive or negative, so those choices don t exist here).

Example 2 Find the square root of 0. The only square root of 0 is 0 (since 0 is not positive or negative, so those choices don t exist here). BEGINNING ALGEBRA Roots ad Radicals (revised summer, 00 Olso) Packet to Supplemet the Curret Textbook - Part Review of Square Roots & Irratioals (This portio ca be ay time before Part ad should mostly

More information

Vector Network Analyzer

Vector Network Analyzer Cours on Microwav Masurmnts Vctor Ntwork Analyzr Prof. Luca Prrgrini Dpt. of Elctrical, Computr and Biomdical Enginring Univrsity of Pavia -mail: luca.prrgrini@unipv.it wb: microwav.unipv.it Microwav Masurmnts

More information

Building Blocks Problem Related to Harmonic Series

Building Blocks Problem Related to Harmonic Series TMME, vol3, o, p.76 Buildig Blocks Problem Related to Harmoic Series Yutaka Nishiyama Osaka Uiversity of Ecoomics, Japa Abstract: I this discussio I give a eplaatio of the divergece ad covergece of ifiite

More information

Elementary Theory of Russian Roulette

Elementary Theory of Russian Roulette Elemetary Theory of Russia Roulette -iterestig patters of fractios- Satoshi Hashiba Daisuke Miematsu Ryohei Miyadera Itroductio. Today we are goig to study mathematical theory of Russia roulette. If some

More information

Repeating Decimals are decimal numbers that have number(s) after the decimal point that repeat in a pattern.

Repeating Decimals are decimal numbers that have number(s) after the decimal point that repeat in a pattern. 5.5 Fractios ad Decimals Steps for Chagig a Fractio to a Decimal. Simplify the fractio, if possible. 2. Divide the umerator by the deomiator. d d Repeatig Decimals Repeatig Decimals are decimal umbers

More information

WORKERS' COMPENSATION ANALYST, 1774 SENIOR WORKERS' COMPENSATION ANALYST, 1769

WORKERS' COMPENSATION ANALYST, 1774 SENIOR WORKERS' COMPENSATION ANALYST, 1769 08-16-85 WORKERS' COMPENSATION ANALYST, 1774 SENIOR WORKERS' COMPENSATION ANALYST, 1769 Summary of Dutis : Dtrmins City accptanc of workrs' compnsation cass for injurd mploys; authorizs appropriat tratmnt

More information

Keywords Cloud Computing, Service level agreement, cloud provider, business level policies, performance objectives.

Keywords Cloud Computing, Service level agreement, cloud provider, business level policies, performance objectives. Volum 3, Issu 6, Jun 2013 ISSN: 2277 128X Intrnational Journal of Advancd Rsarch in Computr Scinc and Softwar Enginring Rsarch Papr Availabl onlin at: wwwijarcsscom Dynamic Ranking and Slction of Cloud

More information